Deep learning and automatic differentiation of pancreatic lesions in endoscopic ultrasound - a transatlantic study.

Endoscopic ultrasound (EUS) allows characterization and biopsy of pancreatic lesions. Pancreatic cystic neoplasms (PCN) include in mucinous (M-PCN) and non-mucinous lesions (NM-PCN). Pancreatic ductal adenocarcinoma (P-DAC) is the commonest pancreatic solid lesion (PSL), followed by pancreatic neuroendocrine tumor (P-NET). While EUS is preferred for pancreatic lesion evaluation, its diagnostic accuracy is suboptimal. This multicentric study aims to develop a convolutional neural network (CNN) for detecting and distinguishing PCN (namely M-PCN and NM-PCN) and PSL (particularly P-DAC and P-NET). A CNN was developed with 378 EUS exams from 4 international reference centers (Centro Hospitalar Universitário São João, Hospital Universitario Puerta de Hierro Majadahonda, New York University Hospitals, Hospital das Clínicas FMUSP). 126.000 images were obtained - 19.528 M-PCN, 8.175 NM-PCN, 64.286 P-DAC, 29.153 P-NET and 4.858 normal pancreas images. A trinary CNN differentiated normal pancreas tissue from M-PCN and NM-PCN. A binary CNN distinguished P-DAC from P-NET. The total dataset was divided in a training and testing dataset (used for model's evaluation) in a 90/10% ratio. The model was evaluated through its sensitivity, specificity, positive and negative predictive values and accuracy. The CNN had 99.1% accuracy for identifying normal pancreatic tissue, 99.0% and 99.8% for M-PCN and NM-PCN, respectively. P-DAC and P-NET were distinguished with 94.0% accuracy. Our group developed the first worldwide CNN capable of detecting and differentiating the commonest PCN and PSL in EUS images, using exams from 4 centers in two continents, minimizing the impact of the demographic bias. Larger multicentric studies are needed for technology implementation.

Becalm: Intelligent Monitoring of Respiratory Patients.

The Becalm project is an open and low-cost solution for the remote monitoring of respiratory support therapies like the ones used in COVID-19 patients. Becalm combines a decision-making system based on Case-Based Reasoning with a low-cost, non-invasive mask that enables the remote monitoring, detection, and explanation of risk situations for respiratory patients. This paper first describes the mask and the sensors that allow remote monitoring. Then, it describes the intelligent decision-making system that detects anomalies and raises early warnings. This detection is based on the comparison of cases that represent patients using a set of static variables plus the dynamic vector of the patient time series from sensors. Finally, personalized visual reports are created to explain the causes of the warning, data patterns, and patient context to the healthcare professional. To evaluate the case-based early-warning system, we use a synthetic data generator that simulates patients' clinical evolution from the physiological features and factors described in healthcare literature. This generation process has been verified with a real dataset and allows the validation of the reasoning system with noisy and incomplete data, threshold values, and life/death situations. The evaluation demonstrates promising results and good accuracy (0.91) for the proposed low-cost solution to monitor respiratory patients.

Timing of Thiopurine or Anti-TNF Initiation Is Associated with the Risk of Major Abdominal Surgery in Crohn's Disease: A Retrospective Cohort Study.

INTRODUCTION: Early stages of Crohn's disease [CD] are predominantly inflammatory and early treatment could be useful to change the natural history of CD. We aimed to evaluate the impact of early treatment in our cohort of CD patients. METHODS: We retrospectively reviewed clinical records of all CD patients at our centre who have received immunomodulators. Time from diagnosis to first CD-related major abdominal surgery or end of follow-up was considered. Dates of diagnosis, of starting immunomodulators (thiopurines / anti-tumour necrosis factor [TNF]), and of the first CD-related surgery when appropriate were collected. RESULTS: Of 422 patients who received thiopurines, 189 operated patients started thiopurines after a median of 117 months (interquartile range [IQR] 44-196) since diagnosis; non-operated patients, after a median of 30 months [IQR 6-128], p < 0,005. Odds ratio [OR] for surgery was 1.006 (95% confidence interval [CI]1.004-1008) for each month of delay in starting thiopurines. Among 272 patients who received anti-TNFs, 137 operated patients started anti-TNFs after a median of 166 months [IQR 90-233] since diagnosis; non-operated patients after a median of 59 months [IQR 14-162]; p < 0,005. OR for surgery was 1.008 [95% CI 1.005-1.010] for each month of delay in starting anti-TNFs. Among 467 patients who received thiopurines and/or anti-TNF, 210 operated patients started any immunomodulator after a median of 120 months [IQR 48-197] since diagnosis and non-operated patients after a median of 30 months [IQR 6-126], p < 0,005. OR for surgery was 1.008 [95% CI 1.005-1.010] for each month of delay in starting immunomodulators. CONCLUSIONS: In our experience, time between diagnosis and thiopurine or anti-TNF initiation was associated with the risk of major abdominal surgery in Crohn's disease.